Statistics You Need
Saif Aldeen Saleh AlRyalat, Shaher Momani in A Beginner's Guide to Using Open Access Data, 2019
Sampling is the process of selecting representative elements of a population for inclusion in a study that allows inferences and generalizations about the population without actually examining each element in the population. The first step is to define the target population. For example, if you are studying a condition in a city, then your target population is the city's population; but if you are studying a condition in an entire country, then your target population would be the country's population. After defining your target population, there are two main sampling techniques to follow: probability and nonprobability sampling (Kothari, 2004). Probability sampling (e.g., simple random sampling) is where elements are chosen randomly and every element has an equal and independent chance of being selected. Although this type of sampling is laborious, it is a better representation of your target population. On the other hand, nonprobability sampling (e.g., convenience sampling) is where elements are chosen by nonrandom methods and there is no way of ensuring that every element has an equal chance of being selected. Although this type of sampling is less rigorous, it is also less representative of your target population.
Understanding research
Geraldine Lee-Treweek, Tom Heller, Hilary MacQueen, Julie Stone, Sue Spurr in Complementary and Alternative Medicine: Structures and Safeguards, 2020
Sampling is the selection of particular individuals or results as being representative of all individuals or results. It is an area fraught with hazards. Everybody tends to remember their successes, or instances that illustrate their beliefs particularly well, but the cases that stick in their minds may not represent the true story. If a practitioner sees 10 people who have a particular disease, three may not complete the treatment, five may improve a little and two may improve a great deal. The practitioner will tend to remember the two successful examples and use them as the basis for writing and teaching. Similarly, the hypothetical GP quoted above may tend to remember one or two particularly difficult people who used CAM, and forget the many others who use it without problems or without their GP’s knowledge.
S
Filomena Pereira-Maxwell in Medical Statistics, 2018
The process of selecting a group of individuals from a population, with the aim to use the information provided by the sample to draw conclusions about a source or a target population. In surveys and cross-sectional studies, random and non-random sampling methods are used. Among the former, frequently used methods are simple random sampling, stratified sampling, cluster sampling and multistage sampling. Systematic sampling and quota sampling are examples of non-random methods frequently used in market research. The ability to generalize from sample to population relies on its representativeness or lack of bias. Sampling is not usually employed in comparative studies (with the exception of selection of controls in case-control studies, which may be carried out through sampling), where comparability and internal validity are the main concerns regarding avoidance of bias. See COCHRAN (1977) and LEVY & LEMESHOW (2009) for comprehensive guides to sampling techniques. See also efficiency.
Exploring Perceptions of Parents on the Use of Emergency Department On-site Primary Care Services for the Treatment of Children With Non-urgent Conditions
Published in Comprehensive Child and Adolescent Nursing, 2021
Mfon Sam, Dianne L. Cook, Andrew G. Rowland, James Butler
Random sampling involves some form of random selection of the population members. Each population member has a known and typically equal probability of being selected. Simple random sampling (sometimes referred to simply as random sampling) is the most straightforward type of random sampling. A sampling frame is constructed – that is, a list of all people belonging to the population. Constructing a sampling frame requires knowledge of exactly who is in the population. A sample of a fixed size is selected at random from this list, with all members of the population having the same probability of being selected, independently of all others. The probability that a population member will be chosen is known in advance (Sedgwick, 2013). In contrast, in this study, convenience sampling involved selecting patients because it was convenient and they were easily accessible. Despite the potential limitations of convenience sampling, it is often used to recruit participants to a study because it is easy to do (Sedgwick, 2013).
Interprofessional conflict and conflict management in an educational setting
Published in Medical Teacher, 2019
Michael Broukhim, Francis Yuen, Haley McDermott, Keri Miller, Leslie Merrill, Robin Kennedy, Michael Wilkes
Given the relatively large number of respondents, the researchers compiled a stratified random sample of 45 respondents representing 20% of each of three professions. This included 20 respondents from the “physician” category, 18 from the “nursing” category, and 7 from the “social work” category. Sampled respondents that had incomplete responses were screened out and replaced by other randomly selected samples. Stratified sampling is a probability sampling method. Rubin and Babbie (2015) explain that the process which first “organize(s) the population into homogeneous subsets … and to select the appropriate number of elements from each” (p. 368). Since “a homogeneous population produces samples with smaller sampling errors than does a heterogeneous population” (p. 368) that “a stratified sample is likely be more representative … than a simple random sample” (p. 369).
Application of six sigma and 5 S to improve medication turnaround time
Published in International Journal of Healthcare Management, 2021
Ankit Singh, Shraddha Pradhan, Priya Ravi, Srikrishna Dhale
The prime objective of the study was to identify the major bottlenecks affecting the medication turnaround time and to reduce it with the help of six sigma DMAIC (Define, Measure, Analyse, Implement and Control) approach and ‘5 S’ tool. The study design was cross-sectional and the observation method of data collection is used moreover, the source of data was both primary time tracking sheet and secondary i.e. hospital information system. The duration of data collection was three months. The sampling frame was medication indents issued from the wards. The sampling method chosen was systematic random sampling. The sample size was 300. The unit of data analysis was patients indent picked based on systematic random sampling once the indent was entered into the hospital information system. The whole process was divided into various sub-steps and the time was tracked with the help of the hospital information system. The inclusion criteria consisted of the only general and private wards and the exclusion criteria were indents issued from Intensive care units and Operation Theatres. Data analysis and interpretation were done using Microsoft Excel and SPSS 20. The adopted five phases of DMAIC are described below:
Related Knowledge Centers
- Copper
- Randomization
- Sampling Frame
- Selection Bias
- Stratified Sampling
- Survey Methodology
- Observation
- Acceptance Sampling
- Opinion Poll
- Sampling Fraction